diff --git a/h2o-algos/src/main/java/hex/adaboost/AdaBoost.java b/h2o-algos/src/main/java/hex/adaboost/AdaBoost.java
index 1e461fea578f..89a7e04a938f 100644
--- a/h2o-algos/src/main/java/hex/adaboost/AdaBoost.java
+++ b/h2o-algos/src/main/java/hex/adaboost/AdaBoost.java
@@ -31,7 +31,7 @@
  */
 public class AdaBoost extends ModelBuilder<AdaBoostModel, AdaBoostModel.AdaBoostParameters, AdaBoostModel.AdaBoostOutput> {
     private static final Logger LOG = Logger.getLogger(AdaBoost.class);
-    private static final int MAX_ESTIMATORS = 100_000;
+    private static final int MAX_LEARNERS = 100_000;
 
     private AdaBoostModel _model;
     private String _weightsName = "weights";
@@ -59,9 +59,9 @@ public boolean haveMojo() {
     @Override
     public void init(boolean expensive) {
         super.init(expensive);
-        if(_parms._n_estimators < 1 || _parms._n_estimators > MAX_ESTIMATORS)
+        if(_parms._nlearners < 1 || _parms._nlearners > MAX_LEARNERS)
             error("n_estimators", "Parameter n_estimators must be in interval [1, "
-                    + MAX_ESTIMATORS + "] but it is " + _parms._n_estimators);
+                    + MAX_LEARNERS + "] but it is " + _parms._nlearners);
         if (_parms._weak_learner == AdaBoostModel.Algorithm.AUTO) {
             _parms._weak_learner = AdaBoostModel.Algorithm.DRF;
         }
@@ -96,8 +96,8 @@ public void computeImpl() {
         }
 
         private void buildAdaboost() {
-            _model._output.alphas = new double[(int)_parms._n_estimators];
-            _model._output.models = new Key[(int)_parms._n_estimators];
+            _model._output.alphas = new double[(int)_parms._nlearners];
+            _model._output.models = new Key[(int)_parms._nlearners];
 
             Frame _trainWithWeights;
             if (_parms._weights_column == null) {
@@ -112,7 +112,7 @@ private void buildAdaboost() {
                 _trainWithWeights = _parms.train();
             }
             
-            for (int n = 0; n < _parms._n_estimators; n++) {
+            for (int n = 0; n < _parms._nlearners; n++) {
                 Timer timer = new Timer();
                 ModelBuilder job = chooseWeakLearner(_trainWithWeights);
                 job._parms._seed += n;
@@ -233,7 +233,7 @@ public TwoDimTable createModelSummaryTable() {
                 "");
         int row = 0;
         int col = 0;
-        table.set(row, col++, _parms._n_estimators);
+        table.set(row, col++, _parms._nlearners);
         table.set(row, col++, _parms._learn_rate);
         table.set(row, col++, _parms._weak_learner.toString());
         table.set(row, col, _parms._seed);
diff --git a/h2o-algos/src/main/java/hex/adaboost/AdaBoostModel.java b/h2o-algos/src/main/java/hex/adaboost/AdaBoostModel.java
index e769779d376c..e9789a53088b 100644
--- a/h2o-algos/src/main/java/hex/adaboost/AdaBoostModel.java
+++ b/h2o-algos/src/main/java/hex/adaboost/AdaBoostModel.java
@@ -92,7 +92,7 @@ public static class AdaBoostParameters extends Model.Parameters {
         /**
          * Number of weak learners to train. Defaults to 50.
          */
-        public int _n_estimators;
+        public int _nlearners;
 
         /**
          * Choose a weak learner type. Defaults to DRF.
@@ -121,12 +121,12 @@ public String javaName() {
 
         @Override
         public long progressUnits() {
-            return _n_estimators;
+            return _nlearners;
         }
 
         public AdaBoostParameters() {
             super();
-            _n_estimators = 50;
+            _nlearners = 50;
             _weak_learner = Algorithm.AUTO;
             _learn_rate = 0.5;
         }
diff --git a/h2o-algos/src/test/java/hex/adaboost/AdaBoostTest.java b/h2o-algos/src/test/java/hex/adaboost/AdaBoostTest.java
index 9258b84caf8d..839858ea95d5 100644
--- a/h2o-algos/src/test/java/hex/adaboost/AdaBoostTest.java
+++ b/h2o-algos/src/test/java/hex/adaboost/AdaBoostTest.java
@@ -3,8 +3,6 @@
 import hex.Model;
 import hex.genmodel.algos.tree.SharedTreeSubgraph;
 import hex.tree.drf.DRFModel;
-import hex.tree.gbm.GBM;
-import hex.tree.gbm.GBMModel;
 import org.junit.Before;
 import org.junit.Rule;
 import org.junit.Test;
@@ -49,7 +47,7 @@ public void testBasicTrain() {
             AdaBoostModel.AdaBoostParameters p = new AdaBoostModel.AdaBoostParameters();
             p._train = train._key;
             p._seed = 0xDECAF;
-            p._n_estimators = 50;
+            p._nlearners = 50;
             p._response_column = response;
 
             AdaBoost adaBoost = new AdaBoost(p);
@@ -89,7 +87,7 @@ public void testBasicTrainGLM() {
             AdaBoostModel.AdaBoostParameters p = new AdaBoostModel.AdaBoostParameters();
             p._train = train._key;
             p._seed = 0xDECAF;
-            p._n_estimators = 50;
+            p._nlearners = 50;
             p._weak_learner = AdaBoostModel.Algorithm.GLM;
             p._response_column = response;
 
@@ -113,7 +111,7 @@ public void testBasicTrainLarge() {
             AdaBoostModel.AdaBoostParameters p = new AdaBoostModel.AdaBoostParameters();
             p._train = train._key;
             p._seed = 0xDECAF;
-            p._n_estimators = 50;
+            p._nlearners = 50;
             p._response_column = response;
 
             AdaBoost adaBoost = new AdaBoost(p);
@@ -136,7 +134,7 @@ public void testBasicTrainAndScore() {
             AdaBoostModel.AdaBoostParameters p = new AdaBoostModel.AdaBoostParameters();
             p._train = train._key;
             p._seed = 0xDECAF;
-            p._n_estimators = 50;
+            p._nlearners = 50;
             p._response_column = response;
 
             AdaBoost adaBoost = new AdaBoost(p);
@@ -168,7 +166,7 @@ public void testBasicTrainAndScoreCategorical() {
             AdaBoostModel.AdaBoostParameters p = new AdaBoostModel.AdaBoostParameters();
             p._train = train._key;
             p._seed = 0xDECAF;
-            p._n_estimators = 50;
+            p._nlearners = 50;
             p._response_column = response;
             p._categorical_encoding = Model.Parameters.CategoricalEncodingScheme.OneHotExplicit;
 
@@ -197,7 +195,7 @@ public void testBasicTrainAndScoreLarge() {
             AdaBoostModel.AdaBoostParameters p = new AdaBoostModel.AdaBoostParameters();
             p._train = train._key;
             p._seed = 0xDECAF;
-            p._n_estimators = 50;
+            p._nlearners = 50;
             p._response_column = response;
 
             AdaBoost adaBoost = new AdaBoost(p);
@@ -226,7 +224,7 @@ public void testBasicTrainAirlines() {
             AdaBoostModel.AdaBoostParameters p = new AdaBoostModel.AdaBoostParameters();
             p._train = train._key;
             p._seed = 0xDECAF;
-            p._n_estimators = 50;
+            p._nlearners = 50;
             p._response_column = response;
 
             AdaBoost adaBoost = new AdaBoost(p);
@@ -255,7 +253,7 @@ public void testBasicTrainHiggs() {
             AdaBoostModel.AdaBoostParameters p = new AdaBoostModel.AdaBoostParameters();
             p._train = train._key;
             p._seed = 0xDECAF;
-            p._n_estimators = 50;
+            p._nlearners = 50;
             p._response_column = response;
 
             AdaBoost adaBoost = new AdaBoost(p);
@@ -330,7 +328,7 @@ public void testBasicTrainAndScoreWithExternalWeightsColumn() {
             AdaBoostModel.AdaBoostParameters p = new AdaBoostModel.AdaBoostParameters();
             p._train = train._key;
             p._seed = 0xDECAF;
-            p._n_estimators = 10;
+            p._nlearners = 10;
             p._response_column = response;
 
             AdaBoost adaBoostReference = new AdaBoost(p);
@@ -374,7 +372,7 @@ public void testBasicTrainAndScoreWithCustomWeightsColumn() {
             AdaBoostModel.AdaBoostParameters p = new AdaBoostModel.AdaBoostParameters();
             p._train = train._key;
             p._seed = 0xDECAF;
-            p._n_estimators = 10;
+            p._nlearners = 10;
             p._response_column = response;
 
             AdaBoost adaBoostReference = new AdaBoost(p);
@@ -419,7 +417,7 @@ public void testBasicTrainAndScoreWithDuplicatedWeightsColumn() {
             AdaBoostModel.AdaBoostParameters p = new AdaBoostModel.AdaBoostParameters();
             p._train = train._key;
             p._seed = 0xDECAF;
-            p._n_estimators = 10;
+            p._nlearners = 10;
             p._response_column = response;
             p._ignore_const_cols = false;
 
@@ -447,7 +445,7 @@ public void testBasicTrainAndScoreGLM() {
             AdaBoostModel.AdaBoostParameters p = new AdaBoostModel.AdaBoostParameters();
             p._train = train._key;
             p._seed = 0xDECAF;
-            p._n_estimators = 50;
+            p._nlearners = 50;
             p._weak_learner = AdaBoostModel.Algorithm.GLM;
             p._response_column = response;
 
@@ -473,7 +471,7 @@ public void testBasicTrainAndScoreGBM() {
             AdaBoostModel.AdaBoostParameters p = new AdaBoostModel.AdaBoostParameters();
             p._train = train._key;
             p._seed = 0xDECAF;
-            p._n_estimators = 50;
+            p._nlearners = 50;
             p._weak_learner = AdaBoostModel.Algorithm.GBM;
             p._response_column = response;